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The role of certainty in behaviour change

Disclaimer: This is a “Here are some things” post in which I try to figure out how a bunch of different facts fit together. It’s not terribly coherent.

I wasn’t thinking about this when I wrote it, but it recently occurred to me that, in a certain sense, the solution I proposed to trolley problems is exactly the same as Beeminder.

The sense in which they are exactly the same is that they are both a system for increasing the cost of an action you want to take because you don’t trust your reasoning in the circumstances that you’d want to take it. They’re systems for distorting incentives in order to get you to behave in a certain way.

You can frame a lot of things like this. In a sense the entire justice system can be framed as this (note: I was not explicitly doing so in the trolley problems post because it was expressed in terms of turning yourself in – it’s about what the right moral choice is, not how to get people to choose the right thing to do): You are changing people’s incentives by creating penalties when they behave in ways you don’t want.

My admittedly imperfect understanding of the evidence is that this isn’t a very good model of how a justice system works in practice. Under this theory, increasing the severity of a punishment should significantly increase the incentive to not commit a crime, and thus should decrease the rate of commission of that crime. In practice, rates of committing crimes appear to be relatively unresponsive to this. In particular, the introduction of capital punishment appears to do little to nothing to reduce the homicide rate.

Circling back to Beeminder, how do you square this with the fact that fairly demonstrably if you increase the pledge on a goal you’re less likely to derail on it (at least on an anecdotal basis, but I think this holds true in general from what other people have said and it would make the entire premise of the site fairly questionable if it weren’t true). Increasing the punishment for behaving “wrongly” acts as a good way to make you much more likely to behave correctly.

The difference seems to be certainty. Fundamentally, it appears that at least in the heat of the moment, criminals don’t think they’re going to get caught. If you believe you’re not going to get caught, how much you’re punished when you get caught is basically irrelevant to you and doesn’t force you to consider your behaviour. With Beeminder or a precommitment to always submit yourself to justice, this goes away because you remove the uncertainty.

In general, and this is where my knowledge about the evidence gets super shaky and really needs further research, this seems to hold as a model of criminal behaviour: Increasing the certainty of conviction seems to work much better than increasing the severity of punishment. Essentially you want to cause people’s suspension of disbelief required to think they’ll get away with it until even in the heat of the moment they can’t really believe it. Presumably, once you have managed to consider people that punishment for a crime is certain the severity of that punishment starts to have more of an effect (However, this is entirely theorising and I do not have evidence to back up this claim’s plausibility with regards to the design of actual justice systems, so it should not be trusted too strongly).

(On a social justice note, my understanding is that there’s a lot of things that black people will stringently avoid doing because given the racism inherent in the criminal justice system they are much less likely to get away with it than white people. I don’t have any statistics, only anecdata I have heard, so I don’t want to comment on this further, but people have certainly reported this influencing their behaviour and it is eminently plausible).

The connection between certainty and effectiveness of incentives seems entirely plausible. People who want to do a thing are going to engage in motivated reasoning to allow themselves to do it, which is going to cause them to convince themselves they’ll get away with it if it’s humanly possible for them to believe that (and humans are really good at believing things).

A thing that’s interesting about this is how it’s completely opposite to how rewards work. Rewards are best at changing behaviour if they’re not predictable. It seems that what you want to do is basically only reward people for a behaviour some of the time (I have no idea what the best probability is for this, but that would be really interesting to find out).

I don’t know precisely why this is, but it seems to mesh with my anecdotal experiences of how to create addictions. The most addicting games aren’t the ones that consistently reward you with steady progress but those where you try and fail a lot. Especially when that failure is sometimes because you weren’t good enough and sometimes the game is just like “ha ha. No”.

So there’s a weird sort of duality here: When trying to get you to do less of something you want to do, you want certain costs. When trying to get you do more of something that you don’t want to do, you want uncertain rewards.

Obviously, I’m interested in all of this in the context of behaviour change.

The major source of uncertainty in my attempts at behaviour change is my use of tagtime. It randomly samples me throughout the day and asks me what I’m doing, I reply with various things that I want to track, and these are fed into beeminder goals (I don’t use any tagtime tags that are not hooked up to goals). These are a mix of “Do more” goals (be outside, be in the gym, be doing Anki cards) and do less goals (be on twitter, be sitting down).

The randomness is purely because this is the most efficient way to track things which are fine grained. For example as a result of tagtime I will often squeeze in a couple minutes of anki between things, such as while resting between sets in the gym. It would be inconceivably heavy weight to try to time those in a fine grained way, but tag time just doesn’t care: It works equally well regardless of how my time is sliced up.

The degree of actual uncertainty in tag time behaviour is pretty low in the long run – I have on average more than 300 pings a week, which is enough that the margin of error on most goals is actually pretty low). However, it has the side effect of greatly increasing the amount of perceived uncertainty, which for the purposes of behaviour change seems likely to be what matters.

And my reaction to the pings is correspondingly very different between these behaviours that I’m rewarding and punishing as a result.

With the do more goals each ping is that little surge of pleasure at the reward “Yay, I got points for doing a thing”. It’s not 100% effective for creating behaviour change (in particular recently has been suffering a bit from lack of motivation. In fact this post is only being written because I let my writing time goal suffer so much that I need to write this while on a team offsite in Ibiza to not derail), but it’s been pretty good.

The do less goals my reaction is “Argh, you caught me”.

Fundamentally, tagtime will catch you. There’s no way to beat the system. Yet I still think I can get away with it.

I’m not sure what to do about this. Tagtime is still the best way to track what I’m doing with my time. It’s possible that even just having spelled this out is sufficient, but I’m not convinced it will be.

Still, it’s not like I can’t change my behaviour without the perfect magic set of incentives, but it sure would be nice to have a system that works with the quirks of my brain rather than forcing me to overcome them with sheer stubbornness.

On the plus side, by writing this blog post about motivation I have managed to satisfy my immediate motivation of getting my writing time goal back up to outside of the backpressure zone. So I’ve got that going for me.

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(I have no idea what the best probability is for [random rewards], but that would be really interesting to find out).

ISTR reading that 50% was near optimal, but I can’t find a cite. I think it was in a discussion of game design about how evil Candy Crush are or something. It seems like this would vary a lot by context.